In this webinar, the Anyscale solutions team will guide you through the steps of taking your Python workloads to the cloud. Previous knowledge of Ray is helpful but not required as we demonstrate the concepts behind running distributed loads in the cloud, and how to interact with Ray and Anyscale in your Python code.
Learn about what it takes to run at scale whether you:
Need help distributing Python
Want to supercharge a Jupyter notebook
Have machine learning (ML) processes that you want to operationalize
Charles has been building distributed solutions for about twenty years. With a storied background in databases, data engineering, and enterprise architecture, he joined Anyscale to further his passion for helping organizations solve tough computational and operational problems. Charles has trained hundreds of students in database design and distributed software engineering, and is keen to learn from you and show how Ray can put massive computation in your hands today.
Javier works as a product manager at Anyscale focusing on Anyscale's managed Ray SaaS offering. Prior to joining Anyscale, Javier worked at Confluent, Klarna and McKinsey.